<p>使用PIL的另一个答案显然更简洁。我有一个类似的问题，并有一个ndarray的形象。是的，我的比用户1202136要复杂得多。我发布它只是因为它演示了另一个使用numpy和数组堆栈的解决方案，但是user1202136的解决方案要好得多。</p>
<pre><code> import matplotlib.pyplot as plt
import numpy as np
import scipy.ndimage
def rgba(rgb_img, alpha):
'''
' takes an rgb ndarray r x c x 3 of dtype=uint8
' and adds an alpha 0-255 to each pixel
'''
rows = len(rgb_img) # get image dimensions
columns = len(rgb_img[0])
rgb_flat = rgb_img.reshape([rows * columns, 3]) # list of rgb pixels
a = np.zeros([rows*columns, 1], dtype=np.uint8) # alpha for each pixel
a.fill(alpha)
rgba = np.column_stack([rgb_flat, a]) # place 4th column
return rgba.reshape([rows, columns, 4]) # reform into r x c x 4
def pad_with_transparent_pixels(rgba_img):
'''
' takes an rgba image r x c
' and places within a buffer of [ 0 0 0 0] to become square,
' with sides = diagonal of img
'''
rows = len(rgba_img) # get image dimensions
columns = len(rgba_img[0])
diag = (rows**2 + columns**2)**0.5
diag = int(diag) + 1
top_pad_height = (diag-rows)/2 + 1
left_pad_width = (diag-columns)/2 + 1
top_pad = np.zeros([top_pad_height, diag, 4], dtype=np.uint8)
left_pad = np.zeros([rows, left_pad_width, 4], dtype=np.uint8)
right_pad = np.zeros([rows,
# assures total width of top_pad for row_stack:
diag - left_pad_width - columns,
4 ],
dtype=np.uint8)
center = np.column_stack([left_pad, rgba_img, right_pad])
return np.row_stack([top_pad, center, top_pad])
def clean_rotate(rgba_img,angle):
rows = len(rgba_img)
columns = len(rgba_img[0])
diag = (rows**2 + columns**2)**.5
diag = int(diag)
pad_img = pad_with_transparent_pixels(rgba_img)
rot_img = scipy.ndimage.rotate(pad_img, angle)
rot_img_rows = len(rot_img)
rot_img_columns = len(rot_img[0])
crop_side = max(1,(rot_img_columns - diag) / 2) #max to avoid splicing [:0]
crop_top = max(1,(rot_img_rows - diag) / 2)
print diag, crop_side, crop_top
return rot_img[crop_top:-crop_top,crop_side:-crop_side]
img = plt.imread('C:\\Users\\bbrown\\Desktop\\Maurine.jpg') # read in a jpg
figure, axes = plt.subplots(1, 2) # create 1x2 grid of axes
axes[0].imshow(img) # place image on first axes
rgba_image = rgba(img, 255) # create an opaque rgba image
rot_img = clean_rotate(rgba_image,50)
#make a pattern of 10 images
for i in range(10):
rot_img = clean_rotate(rgba_image,5*i)
axes[1].imshow(rot_img)
plt.show()
</code></pre>
